Results 11 to 20 of about 4,675,099 (276)
Online Remaining Useful Lifetime Prediction Using Support Vector Regression [PDF]
IEEE Transactions on Emerging Topics in Computing, 2022 An accurate prediction of remaining useful lifetime (RUL) in high reliability and safety electronic systems is required due to its wide use in industrial applications. In this paper, we propose a novel methodology for online RUL prediction, using support vector regression (SVR) model.
Antonio Leonel Hernández Martínez +3 more
core +6 more sources
An Explainable Artificial Intelligence Approach for Remaining Useful Life Prediction
Aerospace, 2023 Prognosis and health management depend on sufficient prior knowledge of the degradation process of critical components to predict the remaining useful life. This task is composed of two phases: learning and prediction.
Genane Youness, Adam Aalah
doaj +2 more sources
Robust prediction of remaining useful lifetime of bearings using deep learning [PDF]
Engineering Applications of Artificial Intelligencehis research has been partially funded by the Spanish National Plan of Research, Development and Innovation under the project EDNA (PID2021-124383OB-I00) and the University of Oviedo, Spain. L. Magadán is supported by the Severo Ochoa program (PA-22-BP21-120).
Luis Magadán +2 more
openaire +3 more sources
Prognostics for electronics components of avionics - NASA IGBT accelerated ageing case study [PDF]
, 2013 Insulate gate bipolar transistors (IGBTs) are widely used in electric vehicles, railway locomotive and new generation aircrafts, due to the IGBTs have advantages in small conduction resistance and small drive current.
Xie, Yuan'an
core +7 more sources
Remaining useful lifetime prediction for predictive maintenance in manufacturing [PDF]
Computers & Industrial Engineering, 2023 Traditional maintenance approaches often result in either premature replacement of machine parts or downtime in production lines due to malfunctions. Consequently, these lead to significant amount waste in material, time and, ultimately, money. In this study, a machine learning-based predictive maintenance approach is proposed to predict the Remaining ...
Bernar Tasci, Ammar Omar, Serkan Ayvaz
openaire +4 more sources
A Hybrid Prognostic Methodology and its Application to Well-Controlled Engineering Systems [PDF]
, 2015 This thesis presents a novel hybrid prognostic methodology, integrating physics-based and data-driven prognostic models, to enhance the prognostic accuracy, robustness, and applicability.
Eker, Ömer Faruk
core +7 more sources
IEEE Open Journal of Power Electronics, 2023 This work proposes a deep learning-based model for predicting the lifetime of power devices subjected to power cycling. To this purpose, a neural network based on bidirectional long short-term memory is adopted.
Alessandro Vaccaro +2 more
doaj +1 more source
Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools
2022 IEEE 20th International Conference on Industrial Informatics (INDIN), 2022 Prediction of Remaining Useful Lifetime(RUL) in the modern manufacturing and automation workplace for machines and tools is essential in Industry 4.0. This is clearly evident as continuous tool wear, or worse, sudden machine breakdown will lead to various manufacturing failures which would clearly cause economic loss.
Haoren Guo +5 more
openaire +2 more sources
A machine learning framework for remaining useful lifetime prediction of li-ion batteries using diverse neural networks [PDF]
, 2023 Accurate prediction of the remaining useful life (RUL) of li-ion batteries (LIBs) is essential for enhancing the operational efficiency and safety of LIB-powered applications.
Junghwan, Lee +3 more
core +1 more source
, 2021 Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021).
Jia-Xiang Cheng
core +1 more source